A diachronic study determining syntactic and semantic features of Urdu-English neural machine translation

A diachronic study determining syntactic and semantic features of Urdu-English neural machine translation

Machine translation produces marginal accuracy rates for low-resource languages, but its deep learning model expects to yield improved accuracy with time. This longitudinal study investigates how Google Translate's Urdu-to-English translated output has evolved between 2018 and 2021. Accuracy an...

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Bibliographic Details
Main Authors: Tamkeen Zehra Shah, Muhammad Imran, Sayed M. Ismail
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Heliyon
Subjects:
Neural machine translation
Urdu
Low-resource language
Google translate
Interlinear gloss
Comparative syntax
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023100910

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http://www.sciencedirect.com/science/article/pii/S2405844023100910

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